MRI signal generation is substantially influenced by factors such as water content, iron, myelin, and several other contributors. Iron levels can be directly assessed using mass spectrometry, while the quantitative impacts of myelin's structure and composition remain unknown to a certain extent and are often inferred from theoretical simulations. Additionally, MRI relaxation rates and susceptibility are sensitive to these tissue constituents, but their specificity is limited. In this context, post-mortem investigations utilizing complementary methods such as TEM, LA-ICP-MS, MALDI-MSI, CARS, and SAXS-TT provide unique insights for the validation and understanding of quantitative MRI parameters. However, in-situ post-mortem MRI has to accommodate for factors like variable temperature, deoxygenated blood, and perfusion. Furthermore, the process of formalin fixation introduces a significant confounder, often obstructing direct conclusions. In this presentation, I aim to summarize our work on translating post-mortem MRI findings to in-vivo conditions, outline the analytical methods used to assess brain tissue structure and composition, and discuss potential collaborations with the MPI CBS. [mehr]

Magnetic resonance (MR) imaging technologies provide unique capabilities to probe the mysteries of biological systems, and have enabled novel insights into anatomy, metabolism, and physiology in both health and disease. However, while MRI is decades old, is associated with multiple Nobel prizes (in physics, chemistry, and medicine), and has already revolutionized fields like medicine and neuroscience, current MRI methods are still very far from achieving the full potential of the MRI signal. In particular, traditional methods are based on classical sampling theory, and suffer from fundamental trade-offs between signal-to-noise ratio, spatial resolution, and data acquisition speed. These issues are exacerbated in high-dimensional applications, due to the curse of dimensionality. Our work addresses the limitations of traditional MR imaging using signal processing approaches that are enabled by modern computational capabilities. These approaches are possible because of certain "blessings of dimensionality," e.g., that high-dimensional data often possess unexpectedly simple structure that can be exploited to alleviate classical barriers to fast high-resolution imaging. This seminar will describe approaches we have developed that use novel constrained imaging models to guide the design of new MR data acquisition and image reconstruction methods, and enable substantial acceleration of both low-dimensional and high-dimensional MR imaging experiments. [mehr]

Despite the vital role of scientific software, it remains an overlooked part of research, often developed within short funding periods with little support for long-term maintenance. This results in software that is hard to discover and challenging to install. It also lacks interoperability across different computing systems, hindering its reuse and violating the FAIR principles - which advocate for scientific outputs to be Findable, Accessible, Interoperable, and Reusable. In this talk, I will present our attempts at this problem through the Neurodesk.org project, and I will show what we are planning next. [mehr]

Comprehensive description of brain tissue's microstructure is crucial for studying the normal and diseased brain. In the talk I will present an in-vivo biophysical framework for increasing the specificity of quantitative MRI to distinct microstructural features of brain tissue, such as the lipid composition and the iron homeostasis. This non-invasive approach identifies lipidomic-related changes in the aging human brain, and allows to test different aging theories. This approach also reveals the disrupted iron homeostasis in brain tumors, and provides iron-related information inaccessible by conventional MRI approaches. Finally, I will propose a new MRI protocol, for implementing this qMRI approach at the sub-voxel level. By monitoring microstructural processes in living brains, we hope to gain a quantitative and specific description of brain tissue that until now was possible only post-mortem, and may further advance human brain research. [mehr]